160results about How to "Easy to track" patented technology

The invention relates to the technical field of disease follow-up visit, in particular to a health state assessment system applied to disease follow-up visit, which comprises a data acquisition module, a data preprocessing module, a health state assessment module, a personalized health management suggestion module, a dynamic health risk prediction module and a visualization module, the data acquisition module acquires multi-dimensional data of a patient and performs data fusion and integration, the health state evaluation module evaluates the health state of the patient based on multi-level feature extraction and a deep learning model, and the personalized health management suggestion module combines a health state evaluation result and historical data to obtain a personalized health management suggestion result. Customized health management suggestions are generated through a rule engine, and the dynamic health risk prediction module predicts future health risks of patients and provides real-time early warning by using a time sequence analysis model. The visualization module displays health assessment and management suggestion results through a chart and an interactive interface, and the accuracy and individuation degree of health management are improved.

The invention discloses a block chain-based digital right encryption management method and system, and relates to the technical field of digital right security management. According to the method, a unique identifier is generated for digital asset information through a Hash algorithm, data privacy is ensured by using asymmetric encryption, and asset uniqueness identification and information encryption protection are realized; according to the method, encrypted asset information is subjected to uplink evidence storage through an intelligent contract, node verification is carried out by adopting a consensus algorithm, tampering resistance, authenticity and transparency of the asset information are analyzed, authenticity of digital assets and safety and reliability of storage are guaranteed, legality of ownership transfer is verified through a consensus mechanism when the digital assets are transacted or transferred, and security and reliability of the digital assets are guaranteed. It is ensured that the transaction meets the preset compliance standard, the asset state on the block chain is updated in real time, and the security and compliance of the transaction are improved; the asset ownership history and the transaction path are tracked and recorded through the traceability mechanism of the block chain, and the traceability and transparency of the asset circulation process are realized.

The invention relates to the technical field of data processing, in particular to a real estate surveying and mapping data processing method and system based on intelligent data. The method comprises the following steps: acquiring multi-source real estate surveying and mapping data; performing space-time synchronization on the multi-source real estate surveying and mapping data to generate multi-source real estate surveying and mapping space alignment data; real estate space feature extraction is carried out on the multi-source real estate surveying and mapping space alignment data to obtain real estate space feature data; performing cross-domain feature fusion on the multi-source real estate surveying and mapping data based on the real estate spatial feature data to generate real estate surveying and mapping fusion spatial feature data; public surveying and mapping point confirmation is carried out on the multi-source real estate surveying and mapping data through the real estate surveying and mapping fusion spatial feature data, and real estate surveying and mapping public surveying and mapping point data are obtained. Through multi-source data space-time synchronization, feature fusion, distortion correction, high-dimensional space reconstruction, semantic tag association and chain storage, the efficiency and accuracy of real estate surveying and mapping data processing are improved.

The invention relates to the technical field of multi-round dialogue processing, in particular to a multi-round dialogue processing method based on RAG technology dynamic cue word retrieval. Comprising the following steps of question input by a user, initial retrieval and cue word generation, question splicing and answer generation, historical dialogue management and context coding, multi-round question analysis and retrieval enhancement, complex question decomposition and parallel retrieval, multi-source information fusion and generation model optimization, iterative feedback and model tuning, and exception handling and fault-tolerant mechanism. According to the method, related information is retrieved from an external knowledge base, the model can utilize wider and more specific knowledge to generate answers and better track dialogue history and context, so that answers consistent and coherent with the dialogue history are generated, the model can generate answers on a short input sequence by retrieving and splicing related cue words, and meanwhile, the model can be used for analyzing the dialogue history. Cue words are dynamically generated according to user input and retrieval results, so that the model can better adapt to different dialogue scenes and user requirements.

The invention provides a safety management and control system for an intelligent lock of a transformer substation, and the system comprises an intelligent wearable device which is used for monitoring the physiological data of a wearer in real time; the environment monitoring module is used for monitoring the environment risk of the working area in real time; the video monitoring module is used for monitoring the in-out dynamic state and the behavior standard of the personnel; the intelligent lock linkage management module is used for automatically locking an intelligent lock and giving an alarm according to monitoring results of the intelligent wearable device, the environment monitoring module and the video monitoring module when abnormity is monitored; the risk assessment module is used for establishing a risk assessment model and dynamically adjusting the operation authority of the intelligent lock; and the situation awareness control module is used for changing the operation authority of the intelligent lock according to the situation evaluation result. The invention further discloses a corresponding method. According to the invention, the safety and management efficiency of electric power facilities such as a transformer substation are improved.

The invention discloses a named entity recognition method and system based on a knowledge enhancement pre-training model, relates to the technical field of named entity recognition, and aims to solve the problem that an existing training model cannot perform named entity recognition more accurately. According to the method, the knowledge enhancement pre-training model is introduced, so that the model can learn more priori knowledge and semantic information, the generalization ability of unseen text data is improved, the interpretability of the model is enhanced through the detailed performance evaluation and optimization process, the working mechanism of the model is beneficially understood, and the working efficiency of the model is improved. Therefore, the model is better adjusted and optimized, the generalization ability of the optimized model is also improved, the model can better adapt to different application scenes and data sets, the generation of the monitoring log enables performance analysis and problem tracking to be more convenient, the continuous optimization of the model performance is facilitated, and the optimization efficiency is improved. A standard knowledge enhancement training model can be improved according to user feedback on a target application terminal.

The embodiment of the invention relates to the field of trajectory tracking, and discloses a target detection tracking method, system and device and a storage medium, and the method comprises the steps: obtaining a plurality of image frames in a video or image sequence; performing detection by using a target detection model to obtain feature detection information of each image frame; inputting the feature detection information into a trajectory tracking model for analysis and processing, and establishing and tracking a motion trajectory of the target object; wherein the method specifically comprises the following steps of: associating the target object by utilizing the frame similarity among the plurality of bounding boxes; and establishing and tracking a motion track of the target object based on an association result. According to the method disclosed by the invention, the technical problems that the tracking object is difficult to accurately detect and the calculation time is relatively long and relatively large computing power resources need to be occupied are solved, the computing power can be reasonably distributed, the balance of high-precision detection and real-time monitoring is realized, the target object is quickly sensed in a complex shielding environment, and the target object detection and tracking effect is improved.

The invention relates to the technical field of target tracking, and discloses a target tracking method and device, an intelligent selling cabinet and a storage medium. Performing pixel weighting on the original image data to obtain target image data; performing rotating frame labeling on the target image data to obtain labeling information of the target image data; according to the annotation information, performing feature learning on the target image data to obtain smear feature information; obtaining a target detection model according to the smear feature information; and obtaining a target tracking result according to the target detection model. According to the method, the target image data with the smear features are obtained after pixel weighting is carried out on the original data, then rotating frame labeling and feature learning are carried out on the target image data, so that a target detection model learns recognition of the smear features, and understanding of a target motion mode is enhanced. In this way, the target can be accurately detected and tracked in real time in a complex scene where the target rapidly moves.

The invention discloses a hydraulic mechanical transmission device control method based on optimal trajectory optimization, and relates to the technical field of equipment intelligent auxiliary operation and control, and the method comprises the following steps: S1, building a physical model of a hydraulic mechanical transmission device; s2, taking the shortest motion time, the most smooth trajectory and the minimum energy consumption as optimization objectives, and obtaining an optimal trajectory based on a trajectory planning algorithm combining an improved sparrow algorithm and a quintic non-uniform B-spline curve; s3, oil return control is optimized; and S4, oil inlet control is optimized, specifically, an oil inlet flow controller is optimized based on a time-varying secant obstacle Lyapunov function and an RBF neural network. According to the trajectory planning algorithm, the trajectory of the hydraulic transmission device can be optimized, oil return and oil inlet are optimized based on the optimal trajectory, and working trajectory planning and high-precision control over the hydraulic equipment executing mechanism are achieved.

The invention discloses a semiconductor test management system, relates to the technical field of semiconductor test, and solves the technical problems that performance detection and evaluation in different stages of wafer production are lacked, and it is difficult to detect whether a wafer has performance abnormity in the production stage in time. According to the stage performance evaluation coefficient of the semiconductor wafer of each node, a node early warning module performs stage early warning on the semiconductor wafer with stage performance abnormity, analyzes the comprehensive performance coefficient of the semiconductor wafer, and performs early warning on the semiconductor wafer which does not meet the standard; by monitoring and analyzing stage performance coefficients in real time, semiconductor wafers which do not meet the standard can be quickly identified, measures are taken in advance, and greater loss generated in the subsequent process is avoided. By detecting whether the performance of the wafer is abnormal or not in the production stage, resources can be reasonably allocated, and defective wafers can be centrally processed or re-evaluated instead of wasting time and materials on possibly failed products.

The invention discloses a time-varying parameterization nonlinear system dynamic surface control and simulation method with extended time-varying constraint, and relates to the field of nonlinear system stabilization and control, and the method comprises the steps: introducing a tangent function as nonlinear mapping in a controller design process, a nonlinear parameter system with time-varying parameters and extended full-state time-varying constraints is converted into a new unconstrained parameterized system. In addition, an improved DSC with an error compensation signal is used, and a new adaptive control technology is provided for a converted nonlinear system. The proposed design scheme avoids assuming that a virtual control coefficient and an upper limit thereof are known, and proves that all signals in a closed-loop system are in semi-global end consistency bounded. A simulation result verifies the effectiveness of the method.

The present invention provides a trough-type solar concentrating tracking bracket, wherein the adjustable lens bracket is provided with a running wheel set, and the running wheel set is driven by a motor to drive the adjustable lens bracket to move along an arc track, so that the trough-type concentrator installed on the adjustable lens bracket can rotate according to the change of the sun's position, thereby reflecting the sunlight from the most suitable direction to the solar collector tube. In this way, only the adjustable lens bracket needs to move, thereby avoiding the frequent movement of the solar collector tube, which not only reduces the maintenance and repair work of the collector tube, but also improves the high-pressure resistance of the collector tube, and at the same time greatly reduces or even avoids possible safety hazards. Therefore, the trough-type solar concentrating tracking bracket of the present invention can conveniently track the reflection of the sun, and has good practicality and market value.

The invention discloses a DHCP (Dynamic Host Configuration Protocol) security protection method and device combining an access position and third-party authentication, which effectively identify and prevent the access of illegal equipment through identity authentication and an access position binding mechanism and reduce the possibility of implementing network attacks by fake identity or disguised equipment. And through real-time abnormity monitoring and alarming, the difficulty of tracing after the event is reduced. According to the method, the configuration of the client does not need to be changed, an operator can quickly deploy and implement, and the existing network architecture does not need to be modified on a large scale. Through the automatic authentication and binding process of the system, the operation burden of an administrator is relieved, and the overall management efficiency is improved. According to the embodiment of the invention, through detailed recording and unique binding of each access device, an accurate device access history can be provided, and tracking and responsibility investigation can be conveniently carried out when a security event occurs. The scheme only depends on the existing network facilities, no extra hardware equipment needs to be purchased for implementing the scheme, and the implementation cost is reduced.

The invention provides a collaborative robot man-machine interaction and anti-collision control method and device based on admittance, and relates to the technical field of robot intelligent control. The method comprises the following steps: acquiring control input force; according to the control input force, constructing a relationship between a state variable and control input in the man-machine interaction system; according to the relation, an expected admittance model and a soft saturation function are adopted, and a reference trajectory of the robot end effector is generated; according to the reference trajectory, an Actor-Critic algorithm is adopted, and a reinforcement learning neural network controller based on admittance control is designed; according to the reinforcement learning neural network controller based on admittance control, a control strategy in the man-machine interaction system is adjusted, and an anti-collision strategy in the man-machine interaction system is obtained. According to the invention, the safety and stability of the man-machine interaction system are improved.

The embodiment of the invention discloses a tractor farm tool unit control method and device, electronic equipment and a storage medium. The method comprises the steps that a state space expression of a control system of a tractor farm tool unit is established; the state variables of the control system comprise the tractor course deviation, the farm tool course deviation and the farm tool transverse deviation of the tractor farm tool unit relative to the target operation path, and the control variable of the control system is the front wheel rotation angle of the tractor; acquiring a state feedback controller of the control system by adopting a linear quadratic regulator based on the state space expression; based on the real-time tractor course deviation, the real-time farm tool course deviation and the real-time farm tool transverse deviation, a real-time target front wheel rotation angle is determined through a state feedback controller; and performing real-time regulation and control on the tractor front wheel rotation angle of the tractor farm tool unit based on the real-time target front wheel rotation angle. According to the embodiment of the invention, the farm tool can better track the target operation path.

The invention relates to an intelligent acquisition, analysis, prediction and automatic violation correction method and system based on public traffic violation big data, and belongs to the field of traffic informatization and intelligent management. The objective of the invention is to identify complex and diverse traffic illegal behaviors and analyze massive illegal data. The system comprises data acquisition, processing and storage, analysis and prediction, automatic violation correction and data security. Through multi-source data access, edge calculation and distributed storage, real-time acquisition and efficient processing of illegal behaviors are realized; deep analysis is carried out on the traffic violation data by using deep learning and big data technologies; and through real-time video stream analysis, tracking, recording and evidence obtaining are performed on suspected illegal behaviors. The system adopts a multi-level security protection mechanism, data privacy and security are ensured, and flexible expansion and multi-system collaboration are realized through modular design. Compared with a traditional system, the system has remarkable advantages in the aspects of data acquisition comprehensiveness, processing efficiency, prediction accuracy, violation correction automation, data security and the like.

The invention discloses an electric tool fault type identification method and system based on data driving, which are used in the field of fault identification, and the method comprises the following steps: collecting operation data of an electric nail gun under different environment conditions and operation states; processing including time domain analysis and frequency domain analysis is executed on the operation data, and a waveform index and a rough principal component analysis method are used for extracting a feature set for distinguishing fault types in an analysis processing result; constructing a fault type identification model by using a support vector machine combination of K neighbors; performing fault type detection and recognition on the electric nail gun by using the trained fault type recognition model; and obtaining the fault type of the electric nail gun according to the analysis result. According to the invention, fault type detection and identification are carried out by using the model to quickly and accurately determine the fault type of the electric nail gun, the efficiency and accuracy of fault diagnosis are improved, and the cause and the feature of the fault are obtained by comparing the difference between different fault types.

The invention provides a robot with an unstacking exception handling function, which comprises a sensing unit, a processing unit, a human-computer interface, an input unit, a sending unit, a robot body and a driving unit, and is characterized in that simulation software of the processing unit is used for building a simulation environment according to a real unstacking scene provided by a user and simulating an unstacking process in the real scene in the simulation environment; when abnormity occurs in the unstacking process, whether manual processing is carried out or not is determined according to the type of the unstacking abnormity; if the user selects that manual processing is needed, an exception processing task is issued to a worker in a real environment through a sending unit; and if manual processing is not needed, the driving unit controls the robot body to directly process unstacking abnormity. Therefore, the unstacking process in a real environment can be monitored in real time through the virtual stack type in simulation, remote monitoring of material disassembly is completed, stacking abnormity in the disassembly process is handled in time, and tracking and management of the real stacking process are facilitated.

The invention provides an unstacking exception handling system which comprises a processing unit, a display unit, an input unit and a sending unit, simulation software is loaded in the processing unit and used for building a simulation environment according to a real unstacking scene provided by a user, and the simulation environment is used for simulating the unstacking process in the real scene; when the robot vision system detects that the real environment is abnormal in the unstacking process, an unstacking abnormity prompt pops up in a simulation interface of the display unit; the processing unit receives the unstacking abnormity type fed back by the robot vision system; and according to the type of the unstacking exception, an unstacking exception handling option box pops up, and if the user selects that manual handling is needed, an exception handling task is issued to a worker in a real environment. Therefore, the unstacking process in the real environment can be monitored in real time through the virtual stack type in the simulation, so that a worker is reminded in time to deal with stacking abnormity in the dismounting process, and the real stacking process is tracked and managed conveniently.

The invention provides a kit for detecting IDH1 gene mutation based on a CRISPR (clustered regularly interspaced short palindromic repeats) technology and application, and belongs to the technical field of biological detection. The invention develops a new application of the CRISPR technology in detection of IDH1 gene mutation. The CRISPR-Cas12a protein specifically recognizes and cuts a target sequence under the guidance of crRNA designed for an IDH1 target sequence, and meanwhile, powerful trans-enzyme digestion activity is exerted to cut non-specific single-stranded DNA (ssDNA), so that visual detection of a target gene is realized. According to the invention, the crRNA is optimized, so that the detection efficiency of IDH1-R132H mutation is improved, and the application prospect is wide.

The invention relates to the technical field of data analysis, in particular to an alpine region solar central heating intelligent regulation and control system based on big data, which comprises an acquisition processing unit, an analysis control unit and a decision execution unit. A data storage module in the analysis control unit adopts a distributed architecture to store data, predicts a heating demand and a solar heat collection trend by applying a hybrid algorithm fusing a deep learning neural network and a physical model, generates a control instruction and transmits the control instruction to a heat source adjusting module, and the heat source adjusting module adopts an incremental conductance method to adjust solar heating. And the valve driving module adjusts the opening degree of the valve based on a PID algorithm, and the regulation and control precision and the energy utilization efficiency of the heating system are improved.

The invention relates to the technical field of data processing, in particular to an order data processing method and system based on a block chain. The method comprises the following steps: acquiring a multi-source order data set; performing transaction address analysis on the multi-source order data set to generate order transaction address data; order processing server construction is carried out on the multi-source order data through the order transaction address data, and order processing distribution server data is generated; order processing access frequency analysis is carried out on the multi-source order data set through order processing distribution server data, and order processing access frequency data is generated; and performing order screening on the multi-source order data set based on the order processing access frequency data to generate high-frequency order access data and low-frequency order access data. According to the invention, through optimization of multi-source data integration, order access frequency analysis, transaction synchronization and channel optimization, the reliability and efficiency of order transaction are improved.

The invention belongs to the technical field of automobile software, and relates to a vehicle software flashing method, system and device and a medium. According to the invention, vehicle information and software information are uploaded to the cloud through the MES system and are stored. ECU software is flashed by combining the vehicle information and the software information stored in the cloud through the MFT terminal. And acquiring the flashed vehicle information, the DID information of the ECU software and the flashed data stream, and uploading the information to the cloud. The method comprises the following steps: acquiring effective bit information of DID information of ECU software, acquiring effective bit information of DID information uploaded by an MES system, and judging whether the effective bit information of the DID information of the ECU software is consistent with the effective bit information of the DID information uploaded by the MES system or not. If yes, ECU software flashing is qualified, and a qualified result is sent to the MFT terminal; if not, the ECU software is flashed and written again. According to the invention, accurate and efficient flashing of the vehicle software can be realized, and the phenomenon of missing flashing of the vehicle software is avoided.

The application relates to the technical field of medical devices, and discloses a positioning and tracking device, an optical positioning system and a surgical mechanical arm. The positioning and tracking device comprises a base and multiple groups of tracking arrays, the multiple groups of tracking arrays are arranged around the inside of the base, each group of tracking arrays comprises at least three tracking elements, and all the tracking elements in the same group of tracking arrays define a plane corresponding to a current tracking array. Alternatively, all the tracking elements in the same group of tracking arrays define a curved surface corresponding to the current tracking array. The positioning and tracking device, the optical positioning system and the surgical mechanical arm provided by the application can improve the problem in the related art that when the included angle between a tracking element and an optical tracking sensor changes greatly in the process of movement of an end instrument, the optical tracking sensor cannot acquire the position of the tracking element, so that the pose of the end instrument cannot be recognized.

The embodiment of the application provides a kind of determination method of abnormal request, this method includes: through the tracker deployed in node, corresponding entry is allocated for each request to node and the entry identification of generating entry identification;According to the generation order of entry identification, generate entry identification chain, wherein, entry identification chain includes entry identification and the validity state of entry identification;Through the polling detection of request in timer in tracker, determine timeout request, and the request corresponding to the first entry identification of chain is determined as abnormal request;Wherein, the first entry identification of chain is the earliest generation and the validity state is valid in entry identification chain.The technical problem that related art cannot accurately detect and locate abnormal request under the condition of low resource consumption is solved by the embodiment of the application.

This invention discloses a method and system for no-load voltage build-up and pre-synchronization grid connection control of an AC excitation system. The method includes: acquiring the amplitude and phase of the grid voltage in real time via a phase-locked loop when the speed of the doubly-fed induction motor reaches the synchronous speed range; detecting the rotor mechanical position and calculating the slip angle using an encoder; extracting the fundamental component and correcting the phase of the stator-side no-load voltage; setting a target value for the stator voltage based on grid voltage-oriented control and calculating the target rotor current; constructing an inner-loop control loop for the rotor current, calculating the feedforward decoupling term and performing phase compensation; superimposing an outer-loop control loop for the stator voltage, and correcting the rotor current through closed-loop adjustment to eliminate the deviation between the stator-side no-load voltage and the grid voltage; and closing the grid connection circuit breaker and switching the control mode when the preset synchronization conditions are met. The dual-closed-loop control structure achieves precise no-load voltage build-up and smooth pre-synchronization grid connection of the excitation system, improving the stability and reliability of the grid connection process.

The application discloses a stable domain constraint trajectory planning and control method for a modular distributed electric drive heavy load vehicle, comprising the following steps: constructing a nonlinear dynamics model of the modular distributed electric drive heavy load vehicle, fitting a tire lateral force model through a rational polynomial, and establishing a vehicle system state space expression based on the rational polynomial form; adopting a sum of squares planning method to estimate the stable domain of the vehicle under different vehicle speeds, road adhesion coefficients and front, middle and rear wheel turning angles, and analyzing the influence of each state quantity on the shape and boundary of the stable domain; embedding the stable domain constraint into a trajectory planning layer based on a quintic polynomial to generate an obstacle avoidance trajectory meeting the dynamics stability; designing a multi-axle proportional steering strategy based on a steady state assumption, and combining a nonlinear model predictive controller to realize trajectory tracking control, so that the stability and control feasibility of the vehicle in a high-speed dynamic obstacle avoidance process are ensured. Through construction of a high-speed dynamic obstacle avoidance simulation scene, the effectiveness, stability and control feasibility of the stable domain constraint trajectory planning and control framework are verified.

The present application belongs to the technical field of grinding processing, and discloses a control method of a point cloud polishing remote control system based on a sliding mode and adaptive control. The control method comprises the following steps: S1, establishing a dynamic equation of the remote control system to obtain control equations of a master robot and a slave robot; S2, performing point cloud scanning on a weld to be polished to obtain corresponding point cloud data, calculating the depth gradient, dexterity and stiffness of each point in the point cloud data, setting a starting point and an ending point of polishing, and planning an optimal polishing path; and S3, inputting the control equations obtained in step S1 and the optimal polishing path obtained in step S2 into a controller to control the slave robot to polish. Through the present application, the accuracy of the control algorithm and the optimization of the point cloud path search are combined, and the efficiency of remote operation control under polishing conditions is improved.

This invention discloses a partial discharge (PD) signal denoising method based on image information entropy and multivariate variational mode decomposition (MMD). The method involves converting the noisy signal into a grayscale image, calculating the image information entropy, and optimizing the number of modes K in the MMD by combining Pearson correlation coefficient and execution efficiency to determine the optimal value. The noisy PD signal is then decomposed. The kurtosis value of each intrinsic mode component is calculated, and the nature of the mode component is determined based on a threshold, classifying it as either a dominant PD component or a noise component. A mathematical statistical method using the 3σ criterion is employed to filter out normally distributed white noise. The reconstructed signal is then denoised using an improved wavelet thresholding method to obtain the denoised PD signal. This denoising method accurately reduces noise in noisy PD signals, achieving good noise suppression and restoring the waveform characteristics of the PD signal while maintaining high execution efficiency.

The invention discloses a design method of a switch device for a drainage system, and the switch device configured in the drainage system comprises an input end and an output end, and comprises an on-off element. The opening and closing element has a first state enabling the input end and the output end to be connected and a second state enabling the input end and the output end to be separated, and the two sides of the opening and closing element are subjected to input pressure and control pressure respectively. The control valve is configured to respond to pressure intensity conversion between the input pressure and the control pressure to generate opening and closing actions so as to realize state switching; and meanwhile, the maximum control pressure value borne by the opening and closing element in the second state is set to be associated with the safety threshold value of the input pressure. And the switching device is provided with an'on ' / 'off' associated identifier which respectively corresponds to a first state / a second state under the control of the maximum pressure of the opening and closing element. The device can simulate the physiological urination process of the human body, and the functions of bladder functional exercise and functional recovery are achieved.